An autonomous vehicle is a motorized vehicle that can operate without human conduction. An exemplary autonomous vehicle includes a plurality of sensor systems, such as but not limited to, a lidar sensor system, a camera sensor system, and a radar sensor system, amongst others. The autonomous vehicle operates based upon sensor signals output by the sensor systems.
The sensor signals output by the sensor systems can be utilized by the autonomous vehicle to detect objects in a driving environment surrounding the autonomous vehicle. When planning motion of the autonomous vehicle, an evaluation can be performed to determine whether a proposed location of the autonomous vehicle at a given time intersects a location occupied by a detected object in the environment surrounding the autonomous vehicle. Some conventional techniques utilize geometry checks on objects in the environment surrounding the autonomous vehicle to identify whether a potential location of the autonomous vehicle intersects with locations of these objects in the environment.
Traditional motion planning techniques for identifying intersections between locations of objects detected in the environment surrounding the autonomous vehicle and potential locations of the autonomous vehicle are oftentimes computationally and time intensive. Moreover, a significant number of these queries are commonly performed in a relatively short period of time when generating a motion plan. As the number of queries to be performed in a period of time continues to increase, it is desirable to decrease an amount of time and an amount of consumed computational resources for performance of each query.